Location patterns exploration

Below we can observe different variations of visualisation how different pollutant distributed in each station.

##                nom_cabina qualitat_aire codi_dtes zqa codi_eoi longitud
## 1       Barcelona - Sants          Bona        ID   1  8019042   2.1331
## 2    Barcelona - Eixample       Regular        IH   1  8019043   2.1538
## 3      Barcelona - Gràcia       Regular        IJ   1  8019044   2.1534
## 4  Barcelona - Ciutadella          Bona        IL   1  8019050   2.1874
## 5 Barcelona - Vall Hebron          Bona        IN   1  8019054   2.1480
## 6 Barcelona - Palau Reial          Bona        IZ   1  8019057   2.1151
##   latitud hora_o3 qualitat_o3 valor_o3 hora_no2 qualitat_no2 valor_no2
## 1 41.3788    <NA>        <NA>     <NA>      23h         Bona  86 µg/m³
## 2 41.3853     23h        Bona  3 µg/m³      23h      Regular 112 µg/m³
## 3 41.3987     23h        Bona  3 µg/m³      23h      Regular 113 µg/m³
## 4 41.3864     23h        Bona  2 µg/m³      23h         Bona  74 µg/m³
## 5 41.4261     23h        Bona 10 µg/m³      23h         Bona  67 µg/m³
## 6 41.3875      0h        Bona  1 µg/m³       0h         Bona  65 µg/m³
##   hora_pm10 qualitat_pm10 valor_pm10         generat   dateTime
## 1      <NA>          <NA>       <NA> 01/01/2019 0:00 1546297502
## 2       23h          Bona   36 µg/m³ 01/01/2019 0:00 1546297502
## 3       23h       Regular   39 µg/m³ 01/01/2019 0:00 1546297502
## 4      <NA>          <NA>       <NA> 01/01/2019 0:00 1546297502
## 5       23h          Bona   12 µg/m³ 01/01/2019 0:00 1546297502
## 6        0h          Bona   15 µg/m³ 01/01/2019 0:00 1546297502

There are some NA values. Within this research NA´s will be replaced by zero´s.

## # A tibble: 8 x 5
##   nom_cabina   valor_no2 valor_o3 valor_pm10 total_pollution
##   <chr>            <dbl>    <dbl>      <dbl>           <dbl>
## 1 Ciutadella       27238    16948          0           44186
## 2 Eixample         30405    14252      15456           60113
## 3 Gràcia           28674    15383      15417           59474
## 4 Observ Fabra      7957    42656       7410           58023
## 5 Palau Reial      18357    22085       9395           49837
## 6 Poblenou         30073        0      16344           46417
## 7 Sants            24111        0          0           24111
## 8 Vall Hebron      20314    27610      10440           58364

## # A tibble: 8 x 5
##   nom_cabina   valor_no2 valor_o3 valor_pm10 total_pollution
##   <chr>            <dbl>    <dbl>      <dbl>           <dbl>
## 1 Ciutadella       27238    16948          0           44186
## 2 Eixample         30405    14252      15456           60113
## 3 Gràcia           28674    15383      15417           59474
## 4 Observ Fabra      7957    42656       7410           58023
## 5 Palau Reial      18357    22085       9395           49837
## 6 Poblenou         30073        0      16344           46417
## 7 Sants            24111        0          0           24111
## 8 Vall Hebron      20314    27610      10440           58364

Below we can see data distributiution for each station (zero values are excluded in order to see beter non-zero results).

We can see, that majority of values is distributed between 0 and 100, but there are some unique values around 200, for example for Ciutadella, Eixample and Gracia. It is recommended to double check, if these values are correct or it is just outliers.

Time patterns exploration

Let´s plot pollution level distribution within the day.

We can see, that O3 (tropospheric Ozone), NO2 (Nitrogen dioxide) pollution level varies during the day, but pollution by PM10 (Suspended particles) is almost constant .

Another observation, which we could not clearly see on the bar chart and line chart demonstrates it, that O3 (tropospheric Ozone) and NO2 (Nitrogen dioxide) are codependant pollutants.

It make sence, as the majority of tropospheric ozone formation occurs when nitrogen oxides.

We can see it on plots for all locations except Observ Fabra. This would be interesting to investigate - if it is issue with the data collection or some specifics of the location?

There is no data about tropospheric ozone in Sants and Poblenou, most probably it is data collection issue rather than the fact, that this pollutant is not present in these locations.

__ It is possible to remove any line, by clicking on the pollutant in the legend__

On the charts below we can observe trend of pollution dynamic during the weekdays.

Time Variation for nitrogen dioxide:

Time Variation for tropospheric ozone:

Time Variation for suspended particles:

Time Variation for all pollutants:

As we can see NO2 ((Nitrogen dioxide)) level have spike on Friday afternoon and decreases on Sunday. As it was mentioned above O3 level behaviour looks inversely proportional to NO2 and we can see it on time variation charts as well.

For O3 (tropospheric Ozone) it is opposite - lowest level on Friday and growth on Wed, Thuesday & Sunday.

PM10 (Suspended particles) have low variation, that is why it looked as constant on the bar chart, but here we can see, that there is some trend as well - during Sunday - Monday before noon it has the lowest level.